Steps for a Data Science project
It all starts with asking an interesting question and then…
- Problem definition and planning:
- Identify problem
- List the projects deliverables
- Generate success factors
- Understand each resource and other limitations
- Put together appropriate team
- Create a plan
- Perform a cost/benefit analysis
- Data preparation:
- Access and combine data tables
- Summarize data
- Look for errors
- Transform data
- Segment data
- Analysis:
- Summarize data
- Exploring relationships between attributes
- Grouping the data
- Identifying non-trivial facts, patterns and trends
- Build regression models
- Build classification models Deployment:
- Generate report
- Deploy standalone or integrated decision tool
- Measure impact
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